Instructions to use Matthijs/mms-tts-abi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Matthijs/mms-tts-abi with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="Matthijs/mms-tts-abi")# Load model directly from transformers import AutoTokenizer, AutoModelForTextToWaveform tokenizer = AutoTokenizer.from_pretrained("Matthijs/mms-tts-abi") model = AutoModelForTextToWaveform.from_pretrained("Matthijs/mms-tts-abi", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5dd45406d1d9baecb589880d67826dd3865c2000b38d365447c2f817aadc0721
- Size of remote file:
- 145 MB
- SHA256:
- 23f82bddeae1c0b2d529b6902ee340cf4d0db9a8c2dea1875f33a303556108d1
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